program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3405.2.1"}, {"coremltools-component-torch", "2.8.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})]
{
    func main<ios18>(tensor<fp16, [1, 64, 24]> latent_pred) {
            tensor<int32, [6]> input_1_pad_0 = const()[name = string("input_1_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_1_mode_0 = const()[name = string("input_1_mode_0"), val = string("constant")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 64, 30]> input_1_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_1_mode_0, pad = input_1_pad_0, x = latent_pred)[name = string("input_1_cast_fp16")];
            string input_3_pad_type_0 = const()[name = string("input_3_pad_type_0"), val = string("valid")];
            int32 input_3_groups_0 = const()[name = string("input_3_groups_0"), val = int32(64)];
            tensor<int32, [1]> input_3_strides_0 = const()[name = string("input_3_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_3_dilations_0 = const()[name = string("input_3_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [64, 1, 7]> weight_1_to_fp16 = const()[name = string("weight_1_to_fp16"), val = tensor<fp16, [64, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [64]> model_0_bias_to_fp16 = const()[name = string("model_0_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1024)))];
            tensor<fp16, [1, 64, 24]> input_3_cast_fp16 = conv(bias = model_0_bias_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = weight_1_to_fp16, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string x_3_pad_type_0 = const()[name = string("x_3_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_3_strides_0 = const()[name = string("x_3_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_3_pad_0 = const()[name = string("x_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_3_dilations_0 = const()[name = string("x_3_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_3_groups_0 = const()[name = string("x_3_groups_0"), val = int32(1)];
            tensor<fp16, [1536, 64, 1]> weight_3_to_fp16 = const()[name = string("weight_3_to_fp16"), val = tensor<fp16, [1536, 64, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1216)))];
            tensor<fp16, [1536]> model_1_bias_to_fp16 = const()[name = string("model_1_bias_to_fp16"), val = tensor<fp16, [1536]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(197888)))];
            tensor<fp16, [1, 1536, 24]> x_3_cast_fp16 = conv(bias = model_1_bias_to_fp16, dilations = x_3_dilations_0, groups = x_3_groups_0, pad = x_3_pad_0, pad_type = x_3_pad_type_0, strides = x_3_strides_0, weight = weight_3_to_fp16, x = input_3_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<fp16, [1, 1536, 1]> model_2_block_0_alpha_to_fp16 = const()[name = string("model_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 1536, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(201024)))];
            tensor<fp16, [1, 1536, 24]> var_77_cast_fp16 = mul(x = model_2_block_0_alpha_to_fp16, y = x_3_cast_fp16)[name = string("op_77_cast_fp16")];
            tensor<fp16, [1, 1536, 24]> var_78_cast_fp16 = sin(x = var_77_cast_fp16)[name = string("op_78_cast_fp16")];
            fp16 var_16_promoted_to_fp16 = const()[name = string("op_16_promoted_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 1536, 24]> var_79_cast_fp16 = pow(x = var_78_cast_fp16, y = var_16_promoted_to_fp16)[name = string("op_79_cast_fp16")];
            tensor<fp16, [1, 1536, 1]> var_76_to_fp16 = const()[name = string("op_76_to_fp16"), val = tensor<fp16, [1, 1536, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(204160)))];
            tensor<fp16, [1, 1536, 24]> var_80_cast_fp16 = mul(x = var_76_to_fp16, y = var_79_cast_fp16)[name = string("op_80_cast_fp16")];
            tensor<fp16, [1, 1536, 24]> input_7_cast_fp16 = add(x = x_3_cast_fp16, y = var_80_cast_fp16)[name = string("input_7_cast_fp16")];
            string x_5_pad_type_0 = const()[name = string("x_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_5_strides_0 = const()[name = string("x_5_strides_0"), val = tensor<int32, [1]>([8])];
            tensor<int32, [2]> x_5_pad_0 = const()[name = string("x_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_5_dilations_0 = const()[name = string("x_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_5_groups_0 = const()[name = string("x_5_groups_0"), val = int32(1)];
            tensor<int32, [3]> x_5_has_output_shape_output_shape_0 = const()[name = string("x_5_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 768, 200])];
            tensor<fp16, [1536, 768, 16]> var_82_to_fp16 = const()[name = string("op_82_to_fp16"), val = tensor<fp16, [1536, 768, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(207296)))];
            tensor<fp16, [768]> model_2_block_1_bias_to_fp16 = const()[name = string("model_2_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37956096)))];
            tensor<fp16, [1, 768, 200]> x_5_has_output_shape_cast_fp16 = conv_transpose(bias = model_2_block_1_bias_to_fp16, dilations = x_5_dilations_0, groups = x_5_groups_0, output_shape = x_5_has_output_shape_output_shape_0, pad = x_5_pad_0, pad_type = x_5_pad_type_0, strides = x_5_strides_0, weight = var_82_to_fp16, x = input_7_cast_fp16)[name = string("x_5_has_output_shape_cast_fp16")];
            tensor<int32, [3]> x_7_begin_0 = const()[name = string("x_7_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> x_7_end_0 = const()[name = string("x_7_end_0"), val = tensor<int32, [3]>([1, 768, 192])];
            tensor<bool, [3]> x_7_end_mask_0 = const()[name = string("x_7_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 768, 192]> x_7_cast_fp16 = slice_by_index(begin = x_7_begin_0, end = x_7_end_0, end_mask = x_7_end_mask_0, x = x_5_has_output_shape_cast_fp16)[name = string("x_7_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_2_block_2_block_0_alpha_to_fp16 = const()[name = string("model_2_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37957696)))];
            tensor<fp16, [1, 768, 192]> var_107_cast_fp16 = mul(x = model_2_block_2_block_0_alpha_to_fp16, y = x_7_cast_fp16)[name = string("op_107_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_108_cast_fp16 = sin(x = var_107_cast_fp16)[name = string("op_108_cast_fp16")];
            fp16 var_16_promoted_1_to_fp16 = const()[name = string("op_16_promoted_1_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_109_cast_fp16 = pow(x = var_108_cast_fp16, y = var_16_promoted_1_to_fp16)[name = string("op_109_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_106_to_fp16 = const()[name = string("op_106_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37959296)))];
            tensor<fp16, [1, 768, 192]> var_110_cast_fp16 = mul(x = var_106_to_fp16, y = var_109_cast_fp16)[name = string("op_110_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_9_cast_fp16 = add(x = x_7_cast_fp16, y = var_110_cast_fp16)[name = string("input_9_cast_fp16")];
            tensor<int32, [6]> input_11_pad_0 = const()[name = string("input_11_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_11_mode_0 = const()[name = string("input_11_mode_0"), val = string("constant")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 768, 198]> input_11_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_11_mode_0, pad = input_11_pad_0, x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
            string x_9_pad_type_0 = const()[name = string("x_9_pad_type_0"), val = string("valid")];
            int32 x_9_groups_0 = const()[name = string("x_9_groups_0"), val = int32(768)];
            tensor<int32, [1]> x_9_strides_0 = const()[name = string("x_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_9_pad_0 = const()[name = string("x_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_9_dilations_0 = const()[name = string("x_9_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [768, 1, 7]> weight_5_to_fp16 = const()[name = string("weight_5_to_fp16"), val = tensor<fp16, [768, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37960896)))];
            tensor<fp16, [768]> model_2_block_2_block_1_bias_to_fp16 = const()[name = string("model_2_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37971712)))];
            tensor<fp16, [1, 768, 192]> x_9_cast_fp16 = conv(bias = model_2_block_2_block_1_bias_to_fp16, dilations = x_9_dilations_0, groups = x_9_groups_0, pad = x_9_pad_0, pad_type = x_9_pad_type_0, strides = x_9_strides_0, weight = weight_5_to_fp16, x = input_11_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_2_block_2_block_2_alpha_to_fp16 = const()[name = string("model_2_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37973312)))];
            tensor<fp16, [1, 768, 192]> var_125_cast_fp16 = mul(x = model_2_block_2_block_2_alpha_to_fp16, y = x_9_cast_fp16)[name = string("op_125_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_126_cast_fp16 = sin(x = var_125_cast_fp16)[name = string("op_126_cast_fp16")];
            fp16 var_16_promoted_2_to_fp16 = const()[name = string("op_16_promoted_2_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_127_cast_fp16 = pow(x = var_126_cast_fp16, y = var_16_promoted_2_to_fp16)[name = string("op_127_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_124_to_fp16 = const()[name = string("op_124_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37974912)))];
            tensor<fp16, [1, 768, 192]> var_128_cast_fp16 = mul(x = var_124_to_fp16, y = var_127_cast_fp16)[name = string("op_128_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_13_cast_fp16 = add(x = x_9_cast_fp16, y = var_128_cast_fp16)[name = string("input_13_cast_fp16")];
            string y_1_pad_type_0 = const()[name = string("y_1_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_1_strides_0 = const()[name = string("y_1_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_1_pad_0 = const()[name = string("y_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_1_dilations_0 = const()[name = string("y_1_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_1_groups_0 = const()[name = string("y_1_groups_0"), val = int32(1)];
            tensor<fp16, [768, 768, 1]> weight_7_to_fp16 = const()[name = string("weight_7_to_fp16"), val = tensor<fp16, [768, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(37976512)))];
            tensor<fp16, [768]> model_2_block_2_block_3_bias_to_fp16 = const()[name = string("model_2_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39156224)))];
            tensor<fp16, [1, 768, 192]> y_1_cast_fp16 = conv(bias = model_2_block_2_block_3_bias_to_fp16, dilations = y_1_dilations_0, groups = y_1_groups_0, pad = y_1_pad_0, pad_type = y_1_pad_type_0, strides = y_1_strides_0, weight = weight_7_to_fp16, x = input_13_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<fp16, [1, 768, 192]> x_11_cast_fp16 = add(x = x_7_cast_fp16, y = y_1_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_2_block_3_block_0_alpha_to_fp16 = const()[name = string("model_2_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39157824)))];
            tensor<fp16, [1, 768, 192]> var_157_cast_fp16 = mul(x = model_2_block_3_block_0_alpha_to_fp16, y = x_11_cast_fp16)[name = string("op_157_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_158_cast_fp16 = sin(x = var_157_cast_fp16)[name = string("op_158_cast_fp16")];
            fp16 var_16_promoted_3_to_fp16 = const()[name = string("op_16_promoted_3_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_159_cast_fp16 = pow(x = var_158_cast_fp16, y = var_16_promoted_3_to_fp16)[name = string("op_159_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_156_to_fp16 = const()[name = string("op_156_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39159424)))];
            tensor<fp16, [1, 768, 192]> var_160_cast_fp16 = mul(x = var_156_to_fp16, y = var_159_cast_fp16)[name = string("op_160_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_17_cast_fp16 = add(x = x_11_cast_fp16, y = var_160_cast_fp16)[name = string("input_17_cast_fp16")];
            tensor<int32, [6]> input_19_pad_0 = const()[name = string("input_19_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("constant")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 768, 210]> input_19_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_19_mode_0, pad = input_19_pad_0, x = input_17_cast_fp16)[name = string("input_19_cast_fp16")];
            string x_13_pad_type_0 = const()[name = string("x_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_13_dilations_0 = const()[name = string("x_13_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_13_groups_0 = const()[name = string("x_13_groups_0"), val = int32(768)];
            tensor<int32, [1]> x_13_strides_0 = const()[name = string("x_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_13_pad_0 = const()[name = string("x_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [768, 1, 7]> weight_9_to_fp16 = const()[name = string("weight_9_to_fp16"), val = tensor<fp16, [768, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39161024)))];
            tensor<fp16, [768]> model_2_block_3_block_1_bias_to_fp16 = const()[name = string("model_2_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39171840)))];
            tensor<fp16, [1, 768, 192]> x_13_cast_fp16 = conv(bias = model_2_block_3_block_1_bias_to_fp16, dilations = x_13_dilations_0, groups = x_13_groups_0, pad = x_13_pad_0, pad_type = x_13_pad_type_0, strides = x_13_strides_0, weight = weight_9_to_fp16, x = input_19_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_2_block_3_block_2_alpha_to_fp16 = const()[name = string("model_2_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39173440)))];
            tensor<fp16, [1, 768, 192]> var_175_cast_fp16 = mul(x = model_2_block_3_block_2_alpha_to_fp16, y = x_13_cast_fp16)[name = string("op_175_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_176_cast_fp16 = sin(x = var_175_cast_fp16)[name = string("op_176_cast_fp16")];
            fp16 var_16_promoted_4_to_fp16 = const()[name = string("op_16_promoted_4_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_177_cast_fp16 = pow(x = var_176_cast_fp16, y = var_16_promoted_4_to_fp16)[name = string("op_177_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_174_to_fp16 = const()[name = string("op_174_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39175040)))];
            tensor<fp16, [1, 768, 192]> var_178_cast_fp16 = mul(x = var_174_to_fp16, y = var_177_cast_fp16)[name = string("op_178_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_21_cast_fp16 = add(x = x_13_cast_fp16, y = var_178_cast_fp16)[name = string("input_21_cast_fp16")];
            string y_3_pad_type_0 = const()[name = string("y_3_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_3_strides_0 = const()[name = string("y_3_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_3_pad_0 = const()[name = string("y_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_3_dilations_0 = const()[name = string("y_3_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_3_groups_0 = const()[name = string("y_3_groups_0"), val = int32(1)];
            tensor<fp16, [768, 768, 1]> weight_11_to_fp16 = const()[name = string("weight_11_to_fp16"), val = tensor<fp16, [768, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39176640)))];
            tensor<fp16, [768]> model_2_block_3_block_3_bias_to_fp16 = const()[name = string("model_2_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40356352)))];
            tensor<fp16, [1, 768, 192]> y_3_cast_fp16 = conv(bias = model_2_block_3_block_3_bias_to_fp16, dilations = y_3_dilations_0, groups = y_3_groups_0, pad = y_3_pad_0, pad_type = y_3_pad_type_0, strides = y_3_strides_0, weight = weight_11_to_fp16, x = input_21_cast_fp16)[name = string("y_3_cast_fp16")];
            tensor<fp16, [1, 768, 192]> x_15_cast_fp16 = add(x = x_11_cast_fp16, y = y_3_cast_fp16)[name = string("x_15_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_2_block_4_block_0_alpha_to_fp16 = const()[name = string("model_2_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40357952)))];
            tensor<fp16, [1, 768, 192]> var_207_cast_fp16 = mul(x = model_2_block_4_block_0_alpha_to_fp16, y = x_15_cast_fp16)[name = string("op_207_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_208_cast_fp16 = sin(x = var_207_cast_fp16)[name = string("op_208_cast_fp16")];
            fp16 var_16_promoted_5_to_fp16 = const()[name = string("op_16_promoted_5_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_209_cast_fp16 = pow(x = var_208_cast_fp16, y = var_16_promoted_5_to_fp16)[name = string("op_209_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_206_to_fp16 = const()[name = string("op_206_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40359552)))];
            tensor<fp16, [1, 768, 192]> var_210_cast_fp16 = mul(x = var_206_to_fp16, y = var_209_cast_fp16)[name = string("op_210_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_25_cast_fp16 = add(x = x_15_cast_fp16, y = var_210_cast_fp16)[name = string("input_25_cast_fp16")];
            tensor<int32, [6]> input_27_pad_0 = const()[name = string("input_27_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
            string input_27_mode_0 = const()[name = string("input_27_mode_0"), val = string("constant")];
            fp16 const_6_to_fp16 = const()[name = string("const_6_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 768, 246]> input_27_cast_fp16 = pad(constant_val = const_6_to_fp16, mode = input_27_mode_0, pad = input_27_pad_0, x = input_25_cast_fp16)[name = string("input_27_cast_fp16")];
            string x_17_pad_type_0 = const()[name = string("x_17_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_17_dilations_0 = const()[name = string("x_17_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_17_groups_0 = const()[name = string("x_17_groups_0"), val = int32(768)];
            tensor<int32, [1]> x_17_strides_0 = const()[name = string("x_17_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_17_pad_0 = const()[name = string("x_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [768, 1, 7]> weight_13_to_fp16 = const()[name = string("weight_13_to_fp16"), val = tensor<fp16, [768, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40361152)))];
            tensor<fp16, [768]> model_2_block_4_block_1_bias_to_fp16 = const()[name = string("model_2_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40371968)))];
            tensor<fp16, [1, 768, 192]> x_17_cast_fp16 = conv(bias = model_2_block_4_block_1_bias_to_fp16, dilations = x_17_dilations_0, groups = x_17_groups_0, pad = x_17_pad_0, pad_type = x_17_pad_type_0, strides = x_17_strides_0, weight = weight_13_to_fp16, x = input_27_cast_fp16)[name = string("x_17_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_2_block_4_block_2_alpha_to_fp16 = const()[name = string("model_2_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40373568)))];
            tensor<fp16, [1, 768, 192]> var_225_cast_fp16 = mul(x = model_2_block_4_block_2_alpha_to_fp16, y = x_17_cast_fp16)[name = string("op_225_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_226_cast_fp16 = sin(x = var_225_cast_fp16)[name = string("op_226_cast_fp16")];
            fp16 var_16_promoted_6_to_fp16 = const()[name = string("op_16_promoted_6_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_227_cast_fp16 = pow(x = var_226_cast_fp16, y = var_16_promoted_6_to_fp16)[name = string("op_227_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_224_to_fp16 = const()[name = string("op_224_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40375168)))];
            tensor<fp16, [1, 768, 192]> var_228_cast_fp16 = mul(x = var_224_to_fp16, y = var_227_cast_fp16)[name = string("op_228_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_29_cast_fp16 = add(x = x_17_cast_fp16, y = var_228_cast_fp16)[name = string("input_29_cast_fp16")];
            string y_5_pad_type_0 = const()[name = string("y_5_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_5_strides_0 = const()[name = string("y_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_5_pad_0 = const()[name = string("y_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_5_dilations_0 = const()[name = string("y_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_5_groups_0 = const()[name = string("y_5_groups_0"), val = int32(1)];
            tensor<fp16, [768, 768, 1]> weight_15_to_fp16 = const()[name = string("weight_15_to_fp16"), val = tensor<fp16, [768, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40376768)))];
            tensor<fp16, [768]> model_2_block_4_block_3_bias_to_fp16 = const()[name = string("model_2_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [768]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41556480)))];
            tensor<fp16, [1, 768, 192]> y_5_cast_fp16 = conv(bias = model_2_block_4_block_3_bias_to_fp16, dilations = y_5_dilations_0, groups = y_5_groups_0, pad = y_5_pad_0, pad_type = y_5_pad_type_0, strides = y_5_strides_0, weight = weight_15_to_fp16, x = input_29_cast_fp16)[name = string("y_5_cast_fp16")];
            tensor<fp16, [1, 768, 192]> x_19_cast_fp16 = add(x = x_15_cast_fp16, y = y_5_cast_fp16)[name = string("x_19_cast_fp16")];
            tensor<fp16, [1, 768, 1]> model_3_block_0_alpha_to_fp16 = const()[name = string("model_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41558080)))];
            tensor<fp16, [1, 768, 192]> var_254_cast_fp16 = mul(x = model_3_block_0_alpha_to_fp16, y = x_19_cast_fp16)[name = string("op_254_cast_fp16")];
            tensor<fp16, [1, 768, 192]> var_255_cast_fp16 = sin(x = var_254_cast_fp16)[name = string("op_255_cast_fp16")];
            fp16 var_16_promoted_7_to_fp16 = const()[name = string("op_16_promoted_7_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 768, 192]> var_256_cast_fp16 = pow(x = var_255_cast_fp16, y = var_16_promoted_7_to_fp16)[name = string("op_256_cast_fp16")];
            tensor<fp16, [1, 768, 1]> var_253_to_fp16 = const()[name = string("op_253_to_fp16"), val = tensor<fp16, [1, 768, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41559680)))];
            tensor<fp16, [1, 768, 192]> var_257_cast_fp16 = mul(x = var_253_to_fp16, y = var_256_cast_fp16)[name = string("op_257_cast_fp16")];
            tensor<fp16, [1, 768, 192]> input_33_cast_fp16 = add(x = x_19_cast_fp16, y = var_257_cast_fp16)[name = string("input_33_cast_fp16")];
            string x_21_pad_type_0 = const()[name = string("x_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_21_strides_0 = const()[name = string("x_21_strides_0"), val = tensor<int32, [1]>([8])];
            tensor<int32, [2]> x_21_pad_0 = const()[name = string("x_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_21_dilations_0 = const()[name = string("x_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_21_groups_0 = const()[name = string("x_21_groups_0"), val = int32(1)];
            tensor<int32, [3]> x_21_has_output_shape_output_shape_0 = const()[name = string("x_21_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 384, 1544])];
            tensor<fp16, [768, 384, 16]> var_259_to_fp16 = const()[name = string("op_259_to_fp16"), val = tensor<fp16, [768, 384, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(41561280)))];
            tensor<fp16, [384]> model_3_block_1_bias_to_fp16 = const()[name = string("model_3_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50998528)))];
            tensor<fp16, [1, 384, 1544]> x_21_has_output_shape_cast_fp16 = conv_transpose(bias = model_3_block_1_bias_to_fp16, dilations = x_21_dilations_0, groups = x_21_groups_0, output_shape = x_21_has_output_shape_output_shape_0, pad = x_21_pad_0, pad_type = x_21_pad_type_0, strides = x_21_strides_0, weight = var_259_to_fp16, x = input_33_cast_fp16)[name = string("x_21_has_output_shape_cast_fp16")];
            tensor<int32, [3]> x_23_begin_0 = const()[name = string("x_23_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> x_23_end_0 = const()[name = string("x_23_end_0"), val = tensor<int32, [3]>([1, 384, 1536])];
            tensor<bool, [3]> x_23_end_mask_0 = const()[name = string("x_23_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 384, 1536]> x_23_cast_fp16 = slice_by_index(begin = x_23_begin_0, end = x_23_end_0, end_mask = x_23_end_mask_0, x = x_21_has_output_shape_cast_fp16)[name = string("x_23_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_3_block_2_block_0_alpha_to_fp16 = const()[name = string("model_3_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(50999360)))];
            tensor<fp16, [1, 384, 1536]> var_284_cast_fp16 = mul(x = model_3_block_2_block_0_alpha_to_fp16, y = x_23_cast_fp16)[name = string("op_284_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_285_cast_fp16 = sin(x = var_284_cast_fp16)[name = string("op_285_cast_fp16")];
            fp16 var_16_promoted_8_to_fp16 = const()[name = string("op_16_promoted_8_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_286_cast_fp16 = pow(x = var_285_cast_fp16, y = var_16_promoted_8_to_fp16)[name = string("op_286_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_283_to_fp16 = const()[name = string("op_283_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51000192)))];
            tensor<fp16, [1, 384, 1536]> var_287_cast_fp16 = mul(x = var_283_to_fp16, y = var_286_cast_fp16)[name = string("op_287_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_35_cast_fp16 = add(x = x_23_cast_fp16, y = var_287_cast_fp16)[name = string("input_35_cast_fp16")];
            tensor<int32, [6]> input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_37_mode_0 = const()[name = string("input_37_mode_0"), val = string("constant")];
            fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 384, 1542]> input_37_cast_fp16 = pad(constant_val = const_8_to_fp16, mode = input_37_mode_0, pad = input_37_pad_0, x = input_35_cast_fp16)[name = string("input_37_cast_fp16")];
            string x_25_pad_type_0 = const()[name = string("x_25_pad_type_0"), val = string("valid")];
            int32 x_25_groups_0 = const()[name = string("x_25_groups_0"), val = int32(384)];
            tensor<int32, [1]> x_25_strides_0 = const()[name = string("x_25_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_25_pad_0 = const()[name = string("x_25_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_25_dilations_0 = const()[name = string("x_25_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [384, 1, 7]> weight_17_to_fp16 = const()[name = string("weight_17_to_fp16"), val = tensor<fp16, [384, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51001024)))];
            tensor<fp16, [384]> model_3_block_2_block_1_bias_to_fp16 = const()[name = string("model_3_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51006464)))];
            tensor<fp16, [1, 384, 1536]> x_25_cast_fp16 = conv(bias = model_3_block_2_block_1_bias_to_fp16, dilations = x_25_dilations_0, groups = x_25_groups_0, pad = x_25_pad_0, pad_type = x_25_pad_type_0, strides = x_25_strides_0, weight = weight_17_to_fp16, x = input_37_cast_fp16)[name = string("x_25_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_3_block_2_block_2_alpha_to_fp16 = const()[name = string("model_3_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51007296)))];
            tensor<fp16, [1, 384, 1536]> var_302_cast_fp16 = mul(x = model_3_block_2_block_2_alpha_to_fp16, y = x_25_cast_fp16)[name = string("op_302_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_303_cast_fp16 = sin(x = var_302_cast_fp16)[name = string("op_303_cast_fp16")];
            fp16 var_16_promoted_9_to_fp16 = const()[name = string("op_16_promoted_9_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_304_cast_fp16 = pow(x = var_303_cast_fp16, y = var_16_promoted_9_to_fp16)[name = string("op_304_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_301_to_fp16 = const()[name = string("op_301_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51008128)))];
            tensor<fp16, [1, 384, 1536]> var_305_cast_fp16 = mul(x = var_301_to_fp16, y = var_304_cast_fp16)[name = string("op_305_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_39_cast_fp16 = add(x = x_25_cast_fp16, y = var_305_cast_fp16)[name = string("input_39_cast_fp16")];
            string y_7_pad_type_0 = const()[name = string("y_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_7_strides_0 = const()[name = string("y_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_7_pad_0 = const()[name = string("y_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_7_dilations_0 = const()[name = string("y_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_7_groups_0 = const()[name = string("y_7_groups_0"), val = int32(1)];
            tensor<fp16, [384, 384, 1]> weight_19_to_fp16 = const()[name = string("weight_19_to_fp16"), val = tensor<fp16, [384, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51008960)))];
            tensor<fp16, [384]> model_3_block_2_block_3_bias_to_fp16 = const()[name = string("model_3_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51303936)))];
            tensor<fp16, [1, 384, 1536]> y_7_cast_fp16 = conv(bias = model_3_block_2_block_3_bias_to_fp16, dilations = y_7_dilations_0, groups = y_7_groups_0, pad = y_7_pad_0, pad_type = y_7_pad_type_0, strides = y_7_strides_0, weight = weight_19_to_fp16, x = input_39_cast_fp16)[name = string("y_7_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> x_27_cast_fp16 = add(x = x_23_cast_fp16, y = y_7_cast_fp16)[name = string("x_27_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_3_block_3_block_0_alpha_to_fp16 = const()[name = string("model_3_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51304768)))];
            tensor<fp16, [1, 384, 1536]> var_334_cast_fp16 = mul(x = model_3_block_3_block_0_alpha_to_fp16, y = x_27_cast_fp16)[name = string("op_334_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_335_cast_fp16 = sin(x = var_334_cast_fp16)[name = string("op_335_cast_fp16")];
            fp16 var_16_promoted_10_to_fp16 = const()[name = string("op_16_promoted_10_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_336_cast_fp16 = pow(x = var_335_cast_fp16, y = var_16_promoted_10_to_fp16)[name = string("op_336_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_333_to_fp16 = const()[name = string("op_333_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51305600)))];
            tensor<fp16, [1, 384, 1536]> var_337_cast_fp16 = mul(x = var_333_to_fp16, y = var_336_cast_fp16)[name = string("op_337_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_43_cast_fp16 = add(x = x_27_cast_fp16, y = var_337_cast_fp16)[name = string("input_43_cast_fp16")];
            tensor<int32, [6]> input_45_pad_0 = const()[name = string("input_45_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
            string input_45_mode_0 = const()[name = string("input_45_mode_0"), val = string("constant")];
            fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 384, 1554]> input_45_cast_fp16 = pad(constant_val = const_10_to_fp16, mode = input_45_mode_0, pad = input_45_pad_0, x = input_43_cast_fp16)[name = string("input_45_cast_fp16")];
            string x_29_pad_type_0 = const()[name = string("x_29_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_29_dilations_0 = const()[name = string("x_29_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_29_groups_0 = const()[name = string("x_29_groups_0"), val = int32(384)];
            tensor<int32, [1]> x_29_strides_0 = const()[name = string("x_29_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_29_pad_0 = const()[name = string("x_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [384, 1, 7]> weight_21_to_fp16 = const()[name = string("weight_21_to_fp16"), val = tensor<fp16, [384, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51306432)))];
            tensor<fp16, [384]> model_3_block_3_block_1_bias_to_fp16 = const()[name = string("model_3_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51311872)))];
            tensor<fp16, [1, 384, 1536]> x_29_cast_fp16 = conv(bias = model_3_block_3_block_1_bias_to_fp16, dilations = x_29_dilations_0, groups = x_29_groups_0, pad = x_29_pad_0, pad_type = x_29_pad_type_0, strides = x_29_strides_0, weight = weight_21_to_fp16, x = input_45_cast_fp16)[name = string("x_29_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_3_block_3_block_2_alpha_to_fp16 = const()[name = string("model_3_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51312704)))];
            tensor<fp16, [1, 384, 1536]> var_352_cast_fp16 = mul(x = model_3_block_3_block_2_alpha_to_fp16, y = x_29_cast_fp16)[name = string("op_352_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_353_cast_fp16 = sin(x = var_352_cast_fp16)[name = string("op_353_cast_fp16")];
            fp16 var_16_promoted_11_to_fp16 = const()[name = string("op_16_promoted_11_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_354_cast_fp16 = pow(x = var_353_cast_fp16, y = var_16_promoted_11_to_fp16)[name = string("op_354_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_351_to_fp16 = const()[name = string("op_351_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51313536)))];
            tensor<fp16, [1, 384, 1536]> var_355_cast_fp16 = mul(x = var_351_to_fp16, y = var_354_cast_fp16)[name = string("op_355_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_47_cast_fp16 = add(x = x_29_cast_fp16, y = var_355_cast_fp16)[name = string("input_47_cast_fp16")];
            string y_9_pad_type_0 = const()[name = string("y_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_9_strides_0 = const()[name = string("y_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_9_pad_0 = const()[name = string("y_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_9_dilations_0 = const()[name = string("y_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_9_groups_0 = const()[name = string("y_9_groups_0"), val = int32(1)];
            tensor<fp16, [384, 384, 1]> weight_23_to_fp16 = const()[name = string("weight_23_to_fp16"), val = tensor<fp16, [384, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51314368)))];
            tensor<fp16, [384]> model_3_block_3_block_3_bias_to_fp16 = const()[name = string("model_3_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51609344)))];
            tensor<fp16, [1, 384, 1536]> y_9_cast_fp16 = conv(bias = model_3_block_3_block_3_bias_to_fp16, dilations = y_9_dilations_0, groups = y_9_groups_0, pad = y_9_pad_0, pad_type = y_9_pad_type_0, strides = y_9_strides_0, weight = weight_23_to_fp16, x = input_47_cast_fp16)[name = string("y_9_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> x_31_cast_fp16 = add(x = x_27_cast_fp16, y = y_9_cast_fp16)[name = string("x_31_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_3_block_4_block_0_alpha_to_fp16 = const()[name = string("model_3_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51610176)))];
            tensor<fp16, [1, 384, 1536]> var_384_cast_fp16 = mul(x = model_3_block_4_block_0_alpha_to_fp16, y = x_31_cast_fp16)[name = string("op_384_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_385_cast_fp16 = sin(x = var_384_cast_fp16)[name = string("op_385_cast_fp16")];
            fp16 var_16_promoted_12_to_fp16 = const()[name = string("op_16_promoted_12_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_386_cast_fp16 = pow(x = var_385_cast_fp16, y = var_16_promoted_12_to_fp16)[name = string("op_386_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_383_to_fp16 = const()[name = string("op_383_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51611008)))];
            tensor<fp16, [1, 384, 1536]> var_387_cast_fp16 = mul(x = var_383_to_fp16, y = var_386_cast_fp16)[name = string("op_387_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_51_cast_fp16 = add(x = x_31_cast_fp16, y = var_387_cast_fp16)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("constant")];
            fp16 const_12_to_fp16 = const()[name = string("const_12_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 384, 1590]> input_53_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string x_33_pad_type_0 = const()[name = string("x_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_33_dilations_0 = const()[name = string("x_33_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_33_groups_0 = const()[name = string("x_33_groups_0"), val = int32(384)];
            tensor<int32, [1]> x_33_strides_0 = const()[name = string("x_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_33_pad_0 = const()[name = string("x_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [384, 1, 7]> weight_25_to_fp16 = const()[name = string("weight_25_to_fp16"), val = tensor<fp16, [384, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51611840)))];
            tensor<fp16, [384]> model_3_block_4_block_1_bias_to_fp16 = const()[name = string("model_3_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51617280)))];
            tensor<fp16, [1, 384, 1536]> x_33_cast_fp16 = conv(bias = model_3_block_4_block_1_bias_to_fp16, dilations = x_33_dilations_0, groups = x_33_groups_0, pad = x_33_pad_0, pad_type = x_33_pad_type_0, strides = x_33_strides_0, weight = weight_25_to_fp16, x = input_53_cast_fp16)[name = string("x_33_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_3_block_4_block_2_alpha_to_fp16 = const()[name = string("model_3_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51618112)))];
            tensor<fp16, [1, 384, 1536]> var_402_cast_fp16 = mul(x = model_3_block_4_block_2_alpha_to_fp16, y = x_33_cast_fp16)[name = string("op_402_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_403_cast_fp16 = sin(x = var_402_cast_fp16)[name = string("op_403_cast_fp16")];
            fp16 var_16_promoted_13_to_fp16 = const()[name = string("op_16_promoted_13_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_404_cast_fp16 = pow(x = var_403_cast_fp16, y = var_16_promoted_13_to_fp16)[name = string("op_404_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_401_to_fp16 = const()[name = string("op_401_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51618944)))];
            tensor<fp16, [1, 384, 1536]> var_405_cast_fp16 = mul(x = var_401_to_fp16, y = var_404_cast_fp16)[name = string("op_405_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_55_cast_fp16 = add(x = x_33_cast_fp16, y = var_405_cast_fp16)[name = string("input_55_cast_fp16")];
            string y_11_pad_type_0 = const()[name = string("y_11_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_11_strides_0 = const()[name = string("y_11_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_11_pad_0 = const()[name = string("y_11_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_11_dilations_0 = const()[name = string("y_11_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_11_groups_0 = const()[name = string("y_11_groups_0"), val = int32(1)];
            tensor<fp16, [384, 384, 1]> weight_27_to_fp16 = const()[name = string("weight_27_to_fp16"), val = tensor<fp16, [384, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51619776)))];
            tensor<fp16, [384]> model_3_block_4_block_3_bias_to_fp16 = const()[name = string("model_3_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [384]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51914752)))];
            tensor<fp16, [1, 384, 1536]> y_11_cast_fp16 = conv(bias = model_3_block_4_block_3_bias_to_fp16, dilations = y_11_dilations_0, groups = y_11_groups_0, pad = y_11_pad_0, pad_type = y_11_pad_type_0, strides = y_11_strides_0, weight = weight_27_to_fp16, x = input_55_cast_fp16)[name = string("y_11_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> x_35_cast_fp16 = add(x = x_31_cast_fp16, y = y_11_cast_fp16)[name = string("x_35_cast_fp16")];
            tensor<fp16, [1, 384, 1]> model_4_block_0_alpha_to_fp16 = const()[name = string("model_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51915584)))];
            tensor<fp16, [1, 384, 1536]> var_431_cast_fp16 = mul(x = model_4_block_0_alpha_to_fp16, y = x_35_cast_fp16)[name = string("op_431_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> var_432_cast_fp16 = sin(x = var_431_cast_fp16)[name = string("op_432_cast_fp16")];
            fp16 var_16_promoted_14_to_fp16 = const()[name = string("op_16_promoted_14_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 384, 1536]> var_433_cast_fp16 = pow(x = var_432_cast_fp16, y = var_16_promoted_14_to_fp16)[name = string("op_433_cast_fp16")];
            tensor<fp16, [1, 384, 1]> var_430_to_fp16 = const()[name = string("op_430_to_fp16"), val = tensor<fp16, [1, 384, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51916416)))];
            tensor<fp16, [1, 384, 1536]> var_434_cast_fp16 = mul(x = var_430_to_fp16, y = var_433_cast_fp16)[name = string("op_434_cast_fp16")];
            tensor<fp16, [1, 384, 1536]> input_59_cast_fp16 = add(x = x_35_cast_fp16, y = var_434_cast_fp16)[name = string("input_59_cast_fp16")];
            string x_37_pad_type_0 = const()[name = string("x_37_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_37_strides_0 = const()[name = string("x_37_strides_0"), val = tensor<int32, [1]>([5])];
            tensor<int32, [2]> x_37_pad_0 = const()[name = string("x_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_37_dilations_0 = const()[name = string("x_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_37_groups_0 = const()[name = string("x_37_groups_0"), val = int32(1)];
            tensor<int32, [3]> x_37_has_output_shape_output_shape_0 = const()[name = string("x_37_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 192, 7685])];
            tensor<fp16, [384, 192, 10]> var_436_to_fp16 = const()[name = string("op_436_to_fp16"), val = tensor<fp16, [384, 192, 10]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(51917248)))];
            tensor<fp16, [192]> model_4_block_1_bias_to_fp16 = const()[name = string("model_4_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53391872)))];
            tensor<fp16, [1, 192, 7685]> x_37_has_output_shape_cast_fp16 = conv_transpose(bias = model_4_block_1_bias_to_fp16, dilations = x_37_dilations_0, groups = x_37_groups_0, output_shape = x_37_has_output_shape_output_shape_0, pad = x_37_pad_0, pad_type = x_37_pad_type_0, strides = x_37_strides_0, weight = var_436_to_fp16, x = input_59_cast_fp16)[name = string("x_37_has_output_shape_cast_fp16")];
            tensor<int32, [3]> x_39_begin_0 = const()[name = string("x_39_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> x_39_end_0 = const()[name = string("x_39_end_0"), val = tensor<int32, [3]>([1, 192, 7680])];
            tensor<bool, [3]> x_39_end_mask_0 = const()[name = string("x_39_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 192, 7680]> x_39_cast_fp16 = slice_by_index(begin = x_39_begin_0, end = x_39_end_0, end_mask = x_39_end_mask_0, x = x_37_has_output_shape_cast_fp16)[name = string("x_39_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_4_block_2_block_0_alpha_to_fp16 = const()[name = string("model_4_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53392320)))];
            tensor<fp16, [1, 192, 7680]> var_461_cast_fp16 = mul(x = model_4_block_2_block_0_alpha_to_fp16, y = x_39_cast_fp16)[name = string("op_461_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_462_cast_fp16 = sin(x = var_461_cast_fp16)[name = string("op_462_cast_fp16")];
            fp16 var_16_promoted_15_to_fp16 = const()[name = string("op_16_promoted_15_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_463_cast_fp16 = pow(x = var_462_cast_fp16, y = var_16_promoted_15_to_fp16)[name = string("op_463_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_460_to_fp16 = const()[name = string("op_460_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53392768)))];
            tensor<fp16, [1, 192, 7680]> var_464_cast_fp16 = mul(x = var_460_to_fp16, y = var_463_cast_fp16)[name = string("op_464_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_61_cast_fp16 = add(x = x_39_cast_fp16, y = var_464_cast_fp16)[name = string("input_61_cast_fp16")];
            tensor<int32, [6]> input_63_pad_0 = const()[name = string("input_63_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_63_mode_0 = const()[name = string("input_63_mode_0"), val = string("constant")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 192, 7686]> input_63_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input_63_mode_0, pad = input_63_pad_0, x = input_61_cast_fp16)[name = string("input_63_cast_fp16")];
            string x_41_pad_type_0 = const()[name = string("x_41_pad_type_0"), val = string("valid")];
            int32 x_41_groups_0 = const()[name = string("x_41_groups_0"), val = int32(192)];
            tensor<int32, [1]> x_41_strides_0 = const()[name = string("x_41_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_41_pad_0 = const()[name = string("x_41_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_41_dilations_0 = const()[name = string("x_41_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [192, 1, 7]> weight_29_to_fp16 = const()[name = string("weight_29_to_fp16"), val = tensor<fp16, [192, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53393216)))];
            tensor<fp16, [192]> model_4_block_2_block_1_bias_to_fp16 = const()[name = string("model_4_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53395968)))];
            tensor<fp16, [1, 192, 7680]> x_41_cast_fp16 = conv(bias = model_4_block_2_block_1_bias_to_fp16, dilations = x_41_dilations_0, groups = x_41_groups_0, pad = x_41_pad_0, pad_type = x_41_pad_type_0, strides = x_41_strides_0, weight = weight_29_to_fp16, x = input_63_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_4_block_2_block_2_alpha_to_fp16 = const()[name = string("model_4_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53396416)))];
            tensor<fp16, [1, 192, 7680]> var_479_cast_fp16 = mul(x = model_4_block_2_block_2_alpha_to_fp16, y = x_41_cast_fp16)[name = string("op_479_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_480_cast_fp16 = sin(x = var_479_cast_fp16)[name = string("op_480_cast_fp16")];
            fp16 var_16_promoted_16_to_fp16 = const()[name = string("op_16_promoted_16_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_481_cast_fp16 = pow(x = var_480_cast_fp16, y = var_16_promoted_16_to_fp16)[name = string("op_481_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_478_to_fp16 = const()[name = string("op_478_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53396864)))];
            tensor<fp16, [1, 192, 7680]> var_482_cast_fp16 = mul(x = var_478_to_fp16, y = var_481_cast_fp16)[name = string("op_482_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_65_cast_fp16 = add(x = x_41_cast_fp16, y = var_482_cast_fp16)[name = string("input_65_cast_fp16")];
            string y_13_pad_type_0 = const()[name = string("y_13_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_13_strides_0 = const()[name = string("y_13_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_13_pad_0 = const()[name = string("y_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_13_dilations_0 = const()[name = string("y_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_13_groups_0 = const()[name = string("y_13_groups_0"), val = int32(1)];
            tensor<fp16, [192, 192, 1]> weight_31_to_fp16 = const()[name = string("weight_31_to_fp16"), val = tensor<fp16, [192, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53397312)))];
            tensor<fp16, [192]> model_4_block_2_block_3_bias_to_fp16 = const()[name = string("model_4_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53471104)))];
            tensor<fp16, [1, 192, 7680]> y_13_cast_fp16 = conv(bias = model_4_block_2_block_3_bias_to_fp16, dilations = y_13_dilations_0, groups = y_13_groups_0, pad = y_13_pad_0, pad_type = y_13_pad_type_0, strides = y_13_strides_0, weight = weight_31_to_fp16, x = input_65_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> x_43_cast_fp16 = add(x = x_39_cast_fp16, y = y_13_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_4_block_3_block_0_alpha_to_fp16 = const()[name = string("model_4_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53471552)))];
            tensor<fp16, [1, 192, 7680]> var_511_cast_fp16 = mul(x = model_4_block_3_block_0_alpha_to_fp16, y = x_43_cast_fp16)[name = string("op_511_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_512_cast_fp16 = sin(x = var_511_cast_fp16)[name = string("op_512_cast_fp16")];
            fp16 var_16_promoted_17_to_fp16 = const()[name = string("op_16_promoted_17_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_513_cast_fp16 = pow(x = var_512_cast_fp16, y = var_16_promoted_17_to_fp16)[name = string("op_513_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_510_to_fp16 = const()[name = string("op_510_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53472000)))];
            tensor<fp16, [1, 192, 7680]> var_514_cast_fp16 = mul(x = var_510_to_fp16, y = var_513_cast_fp16)[name = string("op_514_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_69_cast_fp16 = add(x = x_43_cast_fp16, y = var_514_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_71_pad_0 = const()[name = string("input_71_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
            string input_71_mode_0 = const()[name = string("input_71_mode_0"), val = string("constant")];
            fp16 const_16_to_fp16 = const()[name = string("const_16_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 192, 7698]> input_71_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input_71_mode_0, pad = input_71_pad_0, x = input_69_cast_fp16)[name = string("input_71_cast_fp16")];
            string x_45_pad_type_0 = const()[name = string("x_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_45_dilations_0 = const()[name = string("x_45_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_45_groups_0 = const()[name = string("x_45_groups_0"), val = int32(192)];
            tensor<int32, [1]> x_45_strides_0 = const()[name = string("x_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_45_pad_0 = const()[name = string("x_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [192, 1, 7]> weight_33_to_fp16 = const()[name = string("weight_33_to_fp16"), val = tensor<fp16, [192, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53472448)))];
            tensor<fp16, [192]> model_4_block_3_block_1_bias_to_fp16 = const()[name = string("model_4_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53475200)))];
            tensor<fp16, [1, 192, 7680]> x_45_cast_fp16 = conv(bias = model_4_block_3_block_1_bias_to_fp16, dilations = x_45_dilations_0, groups = x_45_groups_0, pad = x_45_pad_0, pad_type = x_45_pad_type_0, strides = x_45_strides_0, weight = weight_33_to_fp16, x = input_71_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_4_block_3_block_2_alpha_to_fp16 = const()[name = string("model_4_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53475648)))];
            tensor<fp16, [1, 192, 7680]> var_529_cast_fp16 = mul(x = model_4_block_3_block_2_alpha_to_fp16, y = x_45_cast_fp16)[name = string("op_529_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_530_cast_fp16 = sin(x = var_529_cast_fp16)[name = string("op_530_cast_fp16")];
            fp16 var_16_promoted_18_to_fp16 = const()[name = string("op_16_promoted_18_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_531_cast_fp16 = pow(x = var_530_cast_fp16, y = var_16_promoted_18_to_fp16)[name = string("op_531_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_528_to_fp16 = const()[name = string("op_528_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53476096)))];
            tensor<fp16, [1, 192, 7680]> var_532_cast_fp16 = mul(x = var_528_to_fp16, y = var_531_cast_fp16)[name = string("op_532_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_73_cast_fp16 = add(x = x_45_cast_fp16, y = var_532_cast_fp16)[name = string("input_73_cast_fp16")];
            string y_15_pad_type_0 = const()[name = string("y_15_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_15_strides_0 = const()[name = string("y_15_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_15_pad_0 = const()[name = string("y_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_15_dilations_0 = const()[name = string("y_15_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_15_groups_0 = const()[name = string("y_15_groups_0"), val = int32(1)];
            tensor<fp16, [192, 192, 1]> weight_35_to_fp16 = const()[name = string("weight_35_to_fp16"), val = tensor<fp16, [192, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53476544)))];
            tensor<fp16, [192]> model_4_block_3_block_3_bias_to_fp16 = const()[name = string("model_4_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53550336)))];
            tensor<fp16, [1, 192, 7680]> y_15_cast_fp16 = conv(bias = model_4_block_3_block_3_bias_to_fp16, dilations = y_15_dilations_0, groups = y_15_groups_0, pad = y_15_pad_0, pad_type = y_15_pad_type_0, strides = y_15_strides_0, weight = weight_35_to_fp16, x = input_73_cast_fp16)[name = string("y_15_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> x_47_cast_fp16 = add(x = x_43_cast_fp16, y = y_15_cast_fp16)[name = string("x_47_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_4_block_4_block_0_alpha_to_fp16 = const()[name = string("model_4_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53550784)))];
            tensor<fp16, [1, 192, 7680]> var_561_cast_fp16 = mul(x = model_4_block_4_block_0_alpha_to_fp16, y = x_47_cast_fp16)[name = string("op_561_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_562_cast_fp16 = sin(x = var_561_cast_fp16)[name = string("op_562_cast_fp16")];
            fp16 var_16_promoted_19_to_fp16 = const()[name = string("op_16_promoted_19_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_563_cast_fp16 = pow(x = var_562_cast_fp16, y = var_16_promoted_19_to_fp16)[name = string("op_563_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_560_to_fp16 = const()[name = string("op_560_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53551232)))];
            tensor<fp16, [1, 192, 7680]> var_564_cast_fp16 = mul(x = var_560_to_fp16, y = var_563_cast_fp16)[name = string("op_564_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_77_cast_fp16 = add(x = x_47_cast_fp16, y = var_564_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<int32, [6]> input_79_pad_0 = const()[name = string("input_79_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
            string input_79_mode_0 = const()[name = string("input_79_mode_0"), val = string("constant")];
            fp16 const_18_to_fp16 = const()[name = string("const_18_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 192, 7734]> input_79_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input_79_mode_0, pad = input_79_pad_0, x = input_77_cast_fp16)[name = string("input_79_cast_fp16")];
            string x_49_pad_type_0 = const()[name = string("x_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_49_dilations_0 = const()[name = string("x_49_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_49_groups_0 = const()[name = string("x_49_groups_0"), val = int32(192)];
            tensor<int32, [1]> x_49_strides_0 = const()[name = string("x_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_49_pad_0 = const()[name = string("x_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [192, 1, 7]> weight_37_to_fp16 = const()[name = string("weight_37_to_fp16"), val = tensor<fp16, [192, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53551680)))];
            tensor<fp16, [192]> model_4_block_4_block_1_bias_to_fp16 = const()[name = string("model_4_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53554432)))];
            tensor<fp16, [1, 192, 7680]> x_49_cast_fp16 = conv(bias = model_4_block_4_block_1_bias_to_fp16, dilations = x_49_dilations_0, groups = x_49_groups_0, pad = x_49_pad_0, pad_type = x_49_pad_type_0, strides = x_49_strides_0, weight = weight_37_to_fp16, x = input_79_cast_fp16)[name = string("x_49_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_4_block_4_block_2_alpha_to_fp16 = const()[name = string("model_4_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53554880)))];
            tensor<fp16, [1, 192, 7680]> var_579_cast_fp16 = mul(x = model_4_block_4_block_2_alpha_to_fp16, y = x_49_cast_fp16)[name = string("op_579_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_580_cast_fp16 = sin(x = var_579_cast_fp16)[name = string("op_580_cast_fp16")];
            fp16 var_16_promoted_20_to_fp16 = const()[name = string("op_16_promoted_20_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_581_cast_fp16 = pow(x = var_580_cast_fp16, y = var_16_promoted_20_to_fp16)[name = string("op_581_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_578_to_fp16 = const()[name = string("op_578_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53555328)))];
            tensor<fp16, [1, 192, 7680]> var_582_cast_fp16 = mul(x = var_578_to_fp16, y = var_581_cast_fp16)[name = string("op_582_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_81_cast_fp16 = add(x = x_49_cast_fp16, y = var_582_cast_fp16)[name = string("input_81_cast_fp16")];
            string y_17_pad_type_0 = const()[name = string("y_17_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_17_strides_0 = const()[name = string("y_17_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_17_pad_0 = const()[name = string("y_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_17_dilations_0 = const()[name = string("y_17_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_17_groups_0 = const()[name = string("y_17_groups_0"), val = int32(1)];
            tensor<fp16, [192, 192, 1]> weight_39_to_fp16 = const()[name = string("weight_39_to_fp16"), val = tensor<fp16, [192, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53555776)))];
            tensor<fp16, [192]> model_4_block_4_block_3_bias_to_fp16 = const()[name = string("model_4_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53629568)))];
            tensor<fp16, [1, 192, 7680]> y_17_cast_fp16 = conv(bias = model_4_block_4_block_3_bias_to_fp16, dilations = y_17_dilations_0, groups = y_17_groups_0, pad = y_17_pad_0, pad_type = y_17_pad_type_0, strides = y_17_strides_0, weight = weight_39_to_fp16, x = input_81_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> x_51_cast_fp16 = add(x = x_47_cast_fp16, y = y_17_cast_fp16)[name = string("x_51_cast_fp16")];
            tensor<fp16, [1, 192, 1]> model_5_block_0_alpha_to_fp16 = const()[name = string("model_5_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53630016)))];
            tensor<fp16, [1, 192, 7680]> var_608_cast_fp16 = mul(x = model_5_block_0_alpha_to_fp16, y = x_51_cast_fp16)[name = string("op_608_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> var_609_cast_fp16 = sin(x = var_608_cast_fp16)[name = string("op_609_cast_fp16")];
            fp16 var_16_promoted_21_to_fp16 = const()[name = string("op_16_promoted_21_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 192, 7680]> var_610_cast_fp16 = pow(x = var_609_cast_fp16, y = var_16_promoted_21_to_fp16)[name = string("op_610_cast_fp16")];
            tensor<fp16, [1, 192, 1]> var_607_to_fp16 = const()[name = string("op_607_to_fp16"), val = tensor<fp16, [1, 192, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53630464)))];
            tensor<fp16, [1, 192, 7680]> var_611_cast_fp16 = mul(x = var_607_to_fp16, y = var_610_cast_fp16)[name = string("op_611_cast_fp16")];
            tensor<fp16, [1, 192, 7680]> input_85_cast_fp16 = add(x = x_51_cast_fp16, y = var_611_cast_fp16)[name = string("input_85_cast_fp16")];
            string x_53_pad_type_0 = const()[name = string("x_53_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_53_strides_0 = const()[name = string("x_53_strides_0"), val = tensor<int32, [1]>([2])];
            tensor<int32, [2]> x_53_pad_0 = const()[name = string("x_53_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_53_dilations_0 = const()[name = string("x_53_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_53_groups_0 = const()[name = string("x_53_groups_0"), val = int32(1)];
            tensor<int32, [3]> x_53_has_output_shape_output_shape_0 = const()[name = string("x_53_has_output_shape_output_shape_0"), val = tensor<int32, [3]>([1, 96, 15362])];
            tensor<fp16, [192, 96, 4]> var_613_to_fp16 = const()[name = string("op_613_to_fp16"), val = tensor<fp16, [192, 96, 4]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53630912)))];
            tensor<fp16, [96]> model_5_block_1_bias_to_fp16 = const()[name = string("model_5_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53778432)))];
            tensor<fp16, [1, 96, 15362]> x_53_has_output_shape_cast_fp16 = conv_transpose(bias = model_5_block_1_bias_to_fp16, dilations = x_53_dilations_0, groups = x_53_groups_0, output_shape = x_53_has_output_shape_output_shape_0, pad = x_53_pad_0, pad_type = x_53_pad_type_0, strides = x_53_strides_0, weight = var_613_to_fp16, x = input_85_cast_fp16)[name = string("x_53_has_output_shape_cast_fp16")];
            tensor<int32, [3]> x_55_begin_0 = const()[name = string("x_55_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> x_55_end_0 = const()[name = string("x_55_end_0"), val = tensor<int32, [3]>([1, 96, 15360])];
            tensor<bool, [3]> x_55_end_mask_0 = const()[name = string("x_55_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [1, 96, 15360]> x_55_cast_fp16 = slice_by_index(begin = x_55_begin_0, end = x_55_end_0, end_mask = x_55_end_mask_0, x = x_53_has_output_shape_cast_fp16)[name = string("x_55_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_5_block_2_block_0_alpha_to_fp16 = const()[name = string("model_5_block_2_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53778688)))];
            tensor<fp16, [1, 96, 15360]> var_638_cast_fp16 = mul(x = model_5_block_2_block_0_alpha_to_fp16, y = x_55_cast_fp16)[name = string("op_638_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_639_cast_fp16 = sin(x = var_638_cast_fp16)[name = string("op_639_cast_fp16")];
            fp16 var_16_promoted_22_to_fp16 = const()[name = string("op_16_promoted_22_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_640_cast_fp16 = pow(x = var_639_cast_fp16, y = var_16_promoted_22_to_fp16)[name = string("op_640_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_637_to_fp16 = const()[name = string("op_637_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53778944)))];
            tensor<fp16, [1, 96, 15360]> var_641_cast_fp16 = mul(x = var_637_to_fp16, y = var_640_cast_fp16)[name = string("op_641_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_87_cast_fp16 = add(x = x_55_cast_fp16, y = var_641_cast_fp16)[name = string("input_87_cast_fp16")];
            tensor<int32, [6]> input_89_pad_0 = const()[name = string("input_89_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_89_mode_0 = const()[name = string("input_89_mode_0"), val = string("constant")];
            fp16 const_20_to_fp16 = const()[name = string("const_20_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 96, 15366]> input_89_cast_fp16 = pad(constant_val = const_20_to_fp16, mode = input_89_mode_0, pad = input_89_pad_0, x = input_87_cast_fp16)[name = string("input_89_cast_fp16")];
            string x_57_pad_type_0 = const()[name = string("x_57_pad_type_0"), val = string("valid")];
            int32 x_57_groups_0 = const()[name = string("x_57_groups_0"), val = int32(96)];
            tensor<int32, [1]> x_57_strides_0 = const()[name = string("x_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_57_pad_0 = const()[name = string("x_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_57_dilations_0 = const()[name = string("x_57_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [96, 1, 7]> weight_41_to_fp16 = const()[name = string("weight_41_to_fp16"), val = tensor<fp16, [96, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53779200)))];
            tensor<fp16, [96]> model_5_block_2_block_1_bias_to_fp16 = const()[name = string("model_5_block_2_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53780608)))];
            tensor<fp16, [1, 96, 15360]> x_57_cast_fp16 = conv(bias = model_5_block_2_block_1_bias_to_fp16, dilations = x_57_dilations_0, groups = x_57_groups_0, pad = x_57_pad_0, pad_type = x_57_pad_type_0, strides = x_57_strides_0, weight = weight_41_to_fp16, x = input_89_cast_fp16)[name = string("x_57_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_5_block_2_block_2_alpha_to_fp16 = const()[name = string("model_5_block_2_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53780864)))];
            tensor<fp16, [1, 96, 15360]> var_656_cast_fp16 = mul(x = model_5_block_2_block_2_alpha_to_fp16, y = x_57_cast_fp16)[name = string("op_656_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_657_cast_fp16 = sin(x = var_656_cast_fp16)[name = string("op_657_cast_fp16")];
            fp16 var_16_promoted_23_to_fp16 = const()[name = string("op_16_promoted_23_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_658_cast_fp16 = pow(x = var_657_cast_fp16, y = var_16_promoted_23_to_fp16)[name = string("op_658_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_655_to_fp16 = const()[name = string("op_655_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53781120)))];
            tensor<fp16, [1, 96, 15360]> var_659_cast_fp16 = mul(x = var_655_to_fp16, y = var_658_cast_fp16)[name = string("op_659_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_91_cast_fp16 = add(x = x_57_cast_fp16, y = var_659_cast_fp16)[name = string("input_91_cast_fp16")];
            string y_19_pad_type_0 = const()[name = string("y_19_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_19_strides_0 = const()[name = string("y_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_19_pad_0 = const()[name = string("y_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_19_dilations_0 = const()[name = string("y_19_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_19_groups_0 = const()[name = string("y_19_groups_0"), val = int32(1)];
            tensor<fp16, [96, 96, 1]> weight_43_to_fp16 = const()[name = string("weight_43_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53781376)))];
            tensor<fp16, [96]> model_5_block_2_block_3_bias_to_fp16 = const()[name = string("model_5_block_2_block_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53799872)))];
            tensor<fp16, [1, 96, 15360]> y_19_cast_fp16 = conv(bias = model_5_block_2_block_3_bias_to_fp16, dilations = y_19_dilations_0, groups = y_19_groups_0, pad = y_19_pad_0, pad_type = y_19_pad_type_0, strides = y_19_strides_0, weight = weight_43_to_fp16, x = input_91_cast_fp16)[name = string("y_19_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> x_59_cast_fp16 = add(x = x_55_cast_fp16, y = y_19_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_5_block_3_block_0_alpha_to_fp16 = const()[name = string("model_5_block_3_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53800128)))];
            tensor<fp16, [1, 96, 15360]> var_688_cast_fp16 = mul(x = model_5_block_3_block_0_alpha_to_fp16, y = x_59_cast_fp16)[name = string("op_688_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_689_cast_fp16 = sin(x = var_688_cast_fp16)[name = string("op_689_cast_fp16")];
            fp16 var_16_promoted_24_to_fp16 = const()[name = string("op_16_promoted_24_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_690_cast_fp16 = pow(x = var_689_cast_fp16, y = var_16_promoted_24_to_fp16)[name = string("op_690_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_687_to_fp16 = const()[name = string("op_687_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53800384)))];
            tensor<fp16, [1, 96, 15360]> var_691_cast_fp16 = mul(x = var_687_to_fp16, y = var_690_cast_fp16)[name = string("op_691_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_95_cast_fp16 = add(x = x_59_cast_fp16, y = var_691_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<int32, [6]> input_97_pad_0 = const()[name = string("input_97_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 18, 0])];
            string input_97_mode_0 = const()[name = string("input_97_mode_0"), val = string("constant")];
            fp16 const_22_to_fp16 = const()[name = string("const_22_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 96, 15378]> input_97_cast_fp16 = pad(constant_val = const_22_to_fp16, mode = input_97_mode_0, pad = input_97_pad_0, x = input_95_cast_fp16)[name = string("input_97_cast_fp16")];
            string x_61_pad_type_0 = const()[name = string("x_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_61_dilations_0 = const()[name = string("x_61_dilations_0"), val = tensor<int32, [1]>([3])];
            int32 x_61_groups_0 = const()[name = string("x_61_groups_0"), val = int32(96)];
            tensor<int32, [1]> x_61_strides_0 = const()[name = string("x_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_61_pad_0 = const()[name = string("x_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [96, 1, 7]> weight_45_to_fp16 = const()[name = string("weight_45_to_fp16"), val = tensor<fp16, [96, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53800640)))];
            tensor<fp16, [96]> model_5_block_3_block_1_bias_to_fp16 = const()[name = string("model_5_block_3_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802048)))];
            tensor<fp16, [1, 96, 15360]> x_61_cast_fp16 = conv(bias = model_5_block_3_block_1_bias_to_fp16, dilations = x_61_dilations_0, groups = x_61_groups_0, pad = x_61_pad_0, pad_type = x_61_pad_type_0, strides = x_61_strides_0, weight = weight_45_to_fp16, x = input_97_cast_fp16)[name = string("x_61_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_5_block_3_block_2_alpha_to_fp16 = const()[name = string("model_5_block_3_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802304)))];
            tensor<fp16, [1, 96, 15360]> var_706_cast_fp16 = mul(x = model_5_block_3_block_2_alpha_to_fp16, y = x_61_cast_fp16)[name = string("op_706_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_707_cast_fp16 = sin(x = var_706_cast_fp16)[name = string("op_707_cast_fp16")];
            fp16 var_16_promoted_25_to_fp16 = const()[name = string("op_16_promoted_25_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_708_cast_fp16 = pow(x = var_707_cast_fp16, y = var_16_promoted_25_to_fp16)[name = string("op_708_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_705_to_fp16 = const()[name = string("op_705_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802560)))];
            tensor<fp16, [1, 96, 15360]> var_709_cast_fp16 = mul(x = var_705_to_fp16, y = var_708_cast_fp16)[name = string("op_709_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_99_cast_fp16 = add(x = x_61_cast_fp16, y = var_709_cast_fp16)[name = string("input_99_cast_fp16")];
            string y_21_pad_type_0 = const()[name = string("y_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_21_strides_0 = const()[name = string("y_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_21_pad_0 = const()[name = string("y_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_21_dilations_0 = const()[name = string("y_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_21_groups_0 = const()[name = string("y_21_groups_0"), val = int32(1)];
            tensor<fp16, [96, 96, 1]> weight_47_to_fp16 = const()[name = string("weight_47_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53802816)))];
            tensor<fp16, [96]> model_5_block_3_block_3_bias_to_fp16 = const()[name = string("model_5_block_3_block_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53821312)))];
            tensor<fp16, [1, 96, 15360]> y_21_cast_fp16 = conv(bias = model_5_block_3_block_3_bias_to_fp16, dilations = y_21_dilations_0, groups = y_21_groups_0, pad = y_21_pad_0, pad_type = y_21_pad_type_0, strides = y_21_strides_0, weight = weight_47_to_fp16, x = input_99_cast_fp16)[name = string("y_21_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> x_63_cast_fp16 = add(x = x_59_cast_fp16, y = y_21_cast_fp16)[name = string("x_63_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_5_block_4_block_0_alpha_to_fp16 = const()[name = string("model_5_block_4_block_0_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53821568)))];
            tensor<fp16, [1, 96, 15360]> var_738_cast_fp16 = mul(x = model_5_block_4_block_0_alpha_to_fp16, y = x_63_cast_fp16)[name = string("op_738_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_739_cast_fp16 = sin(x = var_738_cast_fp16)[name = string("op_739_cast_fp16")];
            fp16 var_16_promoted_26_to_fp16 = const()[name = string("op_16_promoted_26_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_740_cast_fp16 = pow(x = var_739_cast_fp16, y = var_16_promoted_26_to_fp16)[name = string("op_740_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_737_to_fp16 = const()[name = string("op_737_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53821824)))];
            tensor<fp16, [1, 96, 15360]> var_741_cast_fp16 = mul(x = var_737_to_fp16, y = var_740_cast_fp16)[name = string("op_741_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_103_cast_fp16 = add(x = x_63_cast_fp16, y = var_741_cast_fp16)[name = string("input_103_cast_fp16")];
            tensor<int32, [6]> input_105_pad_0 = const()[name = string("input_105_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 54, 0])];
            string input_105_mode_0 = const()[name = string("input_105_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 96, 15414]> input_105_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_105_mode_0, pad = input_105_pad_0, x = input_103_cast_fp16)[name = string("input_105_cast_fp16")];
            string x_65_pad_type_0 = const()[name = string("x_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_65_dilations_0 = const()[name = string("x_65_dilations_0"), val = tensor<int32, [1]>([9])];
            int32 x_65_groups_0 = const()[name = string("x_65_groups_0"), val = int32(96)];
            tensor<int32, [1]> x_65_strides_0 = const()[name = string("x_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_65_pad_0 = const()[name = string("x_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [96, 1, 7]> weight_49_to_fp16 = const()[name = string("weight_49_to_fp16"), val = tensor<fp16, [96, 1, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53822080)))];
            tensor<fp16, [96]> model_5_block_4_block_1_bias_to_fp16 = const()[name = string("model_5_block_4_block_1_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53823488)))];
            tensor<fp16, [1, 96, 15360]> x_65_cast_fp16 = conv(bias = model_5_block_4_block_1_bias_to_fp16, dilations = x_65_dilations_0, groups = x_65_groups_0, pad = x_65_pad_0, pad_type = x_65_pad_type_0, strides = x_65_strides_0, weight = weight_49_to_fp16, x = input_105_cast_fp16)[name = string("x_65_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_5_block_4_block_2_alpha_to_fp16 = const()[name = string("model_5_block_4_block_2_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53823744)))];
            tensor<fp16, [1, 96, 15360]> var_756_cast_fp16 = mul(x = model_5_block_4_block_2_alpha_to_fp16, y = x_65_cast_fp16)[name = string("op_756_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_757_cast_fp16 = sin(x = var_756_cast_fp16)[name = string("op_757_cast_fp16")];
            fp16 var_16_promoted_27_to_fp16 = const()[name = string("op_16_promoted_27_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_758_cast_fp16 = pow(x = var_757_cast_fp16, y = var_16_promoted_27_to_fp16)[name = string("op_758_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_755_to_fp16 = const()[name = string("op_755_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53824000)))];
            tensor<fp16, [1, 96, 15360]> var_759_cast_fp16 = mul(x = var_755_to_fp16, y = var_758_cast_fp16)[name = string("op_759_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_107_cast_fp16 = add(x = x_65_cast_fp16, y = var_759_cast_fp16)[name = string("input_107_cast_fp16")];
            string y_pad_type_0 = const()[name = string("y_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> y_strides_0 = const()[name = string("y_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> y_pad_0 = const()[name = string("y_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> y_dilations_0 = const()[name = string("y_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 y_groups_0 = const()[name = string("y_groups_0"), val = int32(1)];
            tensor<fp16, [96, 96, 1]> weight_51_to_fp16 = const()[name = string("weight_51_to_fp16"), val = tensor<fp16, [96, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53824256)))];
            tensor<fp16, [96]> model_5_block_4_block_3_bias_to_fp16 = const()[name = string("model_5_block_4_block_3_bias_to_fp16"), val = tensor<fp16, [96]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53842752)))];
            tensor<fp16, [1, 96, 15360]> y_cast_fp16 = conv(bias = model_5_block_4_block_3_bias_to_fp16, dilations = y_dilations_0, groups = y_groups_0, pad = y_pad_0, pad_type = y_pad_type_0, strides = y_strides_0, weight = weight_51_to_fp16, x = input_107_cast_fp16)[name = string("y_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> x_cast_fp16 = add(x = x_63_cast_fp16, y = y_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [1, 96, 1]> model_6_alpha_to_fp16 = const()[name = string("model_6_alpha_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53843008)))];
            tensor<fp16, [1, 96, 15360]> var_775_cast_fp16 = mul(x = model_6_alpha_to_fp16, y = x_cast_fp16)[name = string("op_775_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> var_776_cast_fp16 = sin(x = var_775_cast_fp16)[name = string("op_776_cast_fp16")];
            fp16 var_16_promoted_28_to_fp16 = const()[name = string("op_16_promoted_28_to_fp16"), val = fp16(0x1p+1)];
            tensor<fp16, [1, 96, 15360]> var_777_cast_fp16 = pow(x = var_776_cast_fp16, y = var_16_promoted_28_to_fp16)[name = string("op_777_cast_fp16")];
            tensor<fp16, [1, 96, 1]> var_774_to_fp16 = const()[name = string("op_774_to_fp16"), val = tensor<fp16, [1, 96, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53843264)))];
            tensor<fp16, [1, 96, 15360]> var_778_cast_fp16 = mul(x = var_774_to_fp16, y = var_777_cast_fp16)[name = string("op_778_cast_fp16")];
            tensor<fp16, [1, 96, 15360]> input_111_cast_fp16 = add(x = x_cast_fp16, y = var_778_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<int32, [6]> input_113_pad_0 = const()[name = string("input_113_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 6, 0])];
            string input_113_mode_0 = const()[name = string("input_113_mode_0"), val = string("constant")];
            fp16 const_26_to_fp16 = const()[name = string("const_26_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 96, 15366]> input_113_cast_fp16 = pad(constant_val = const_26_to_fp16, mode = input_113_mode_0, pad = input_113_pad_0, x = input_111_cast_fp16)[name = string("input_113_cast_fp16")];
            string input_pad_type_0 = const()[name = string("input_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_strides_0 = const()[name = string("input_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_pad_0 = const()[name = string("input_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_dilations_0 = const()[name = string("input_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_groups_0 = const()[name = string("input_groups_0"), val = int32(1)];
            tensor<fp16, [1, 96, 7]> weight_to_fp16 = const()[name = string("weight_to_fp16"), val = tensor<fp16, [1, 96, 7]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53843520)))];
            tensor<fp16, [1]> model_7_bias_to_fp16 = const()[name = string("model_7_bias_to_fp16"), val = tensor<fp16, [1]>([0x1.108p-13])];
            tensor<fp16, [1, 1, 15360]> input_cast_fp16 = conv(bias = model_7_bias_to_fp16, dilations = input_dilations_0, groups = input_groups_0, pad = input_pad_0, pad_type = input_pad_type_0, strides = input_strides_0, weight = weight_to_fp16, x = input_113_cast_fp16)[name = string("input_cast_fp16")];
            tensor<fp16, [1, 1, 15360]> decoded_audio = tanh(x = input_cast_fp16)[name = string("op_789_cast_fp16")];
        } -> (decoded_audio);
}